Core ConceptsHistory & LandmarksGovernance, Policy & LawPhilosophy & Mind

artificial intelligence

nounAlso: AI, A.I.

In plain wordsComputer systems that do things we would normally credit to a thinking mind, such as holding a conversation, reading an X-ray or planning a route, and the field of research that builds them.

1
Field
The branch of computer science, overlapping with cognitive science, statistics and engineering, devoted to machines that perceive, communicate in language, reason, plan, learn and act purposefully, and to the theory of how such abilities can be computed. Textbook definitions differ in emphasis (thinking or acting, humanlike or rational); the influential framing of Stuart Russell and Peter Norvig treats AI as the study of agentsintelligent agent, n.: In AI theory, a decision-maker, such as a robot, a self-driving car, a chess program or a helpful piece of software, that notices what is going on around it and responds in ways that serve its goals. that act to achieve the best expected outcome. The field's methods have swung between symbolic AIsymbolic AI, n.: An approach to AI that writes knowledge down as human-readable symbols and rules, such as 'every bird has wings', and reasons by manipulating them step by step instead of learning patterns from data. (hand-written rules and logic) and statistical learning. Since the 2010s it has been dominated by machine learningmachine learning, n.: A way of building software that learns from examples instead of following rules written by a programmer. Shown thousands of labeled photos, for instance, a program can learn to recognize cats., especially deep learningdeep learning, n.: Machine learning done with neural networks built from many stacked layers: raw data such as pixels, sound or text goes in at one end, and each layer turns what it receives into something more abstract. and, from about 2020, large language modelslarge language model, n.: A computer program trained on enormous amounts of text to predict the words that come next. At vast scale, that simple skill lets it chat, answer questions, translate, summarize and write code.. Major subfields include computer visioncomputer vision, n.: The part of AI that lets computers make sense of images and video: recognizing faces, reading signs, spotting tumors on scans or judging how far away a car is., natural language processingnatural language processing, n.: The field that teaches computers to handle human language — to read, interpret, translate, summarize and produce text and speech. It is one of the oldest and largest areas of artificial intelligence., roboticsrobotics, n.: The science and engineering of building robots and making them work: designing their bodies, sensors and motors, and writing the software that lets them see, plan and move safely., planningautomated planning, n.: The branch of AI that works out a sequence of actions to reach a goal, such as the steps a robot must take to assemble a part, from descriptions of what each action needs and what it changes., knowledge representationknowledge representation, n.: The study of how to record knowledge about objects, categories, rules and events in a precise format, so that a program can reason with it and reach conclusions nobody typed in. and reinforcement learningreinforcement learning, n.: A way of teaching a computer program by trial and error: it tries actions, earns points for good results and penalties for bad ones, and gradually learns which choices pay off over time..
She moved from physics into artificial intelligence to work on protein-structure prediction.
2
Systems
A machine or program exhibiting such abilities, or such abilities collectively; also a count noun ('an AI', 'AIs') for an individual system, assistant or agent. In everyday and commercial speech the word now usually means generative AIgenerative AI, n.: AI that produces something new on request, such as an essay, a picture, a song or a piece of code, having absorbed from enormous numbers of existing examples what such things typically look like. products built on large language modelslarge language model, n.: A computer program trained on enormous amounts of text to predict the words that come next. At vast scale, that simple skill lets it chat, answer questions, translate, summarize and write code., but it is applied loosely to any software that uses machine learningmachine learning, n.: A way of building software that learns from examples instead of following rules written by a programmer. Shown thousands of labeled photos, for instance, a program can learn to recognize cats., or even plain automation, a looseness criticized as AI washingAI washing, n.: Falsely claiming that a product or company uses AI, or exaggerating how much it does, to look more advanced and attract customers or investors..
The company says an AI now handles first-line customer queries.
3
Lawlegal
In statutes and standards, AI is usually defined as a kind of system rather than a discipline. In United States federal law (15 U.S.C. § 9401(3)) it is a machine-based system that, pursuing objectives set by humans, can 'make predictions, recommendations or decisions influencing real or virtual environments'. The EU AI ActEU AI Act, prop. n.: The European Union's law on artificial intelligence, the first broad AI law anywhere: it bans some uses, sets strict checks for risky ones and puts duties on the makers of the biggest AI models. and the OECD instead define an AI systemAI system, n.: A complete piece of technology that uses AI to do something, such as screening loan applications, driving a car or chatting with customers, including the AI model and the software around it., whose distinguishing trait is inference: it derives from its inputs how to produce outputs, rather than only executing rules written entirely by people.

Origin

Coined by John McCarthy in 'A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence' (31 August 1955), written with Marvin Minsky, Nathaniel Rochester and Claude Shannon; the Dartmouth workshopDartmouth workshop, prop. n.: A summer meeting of scientists at Dartmouth College in 1956, planned in a 1955 funding proposal that first used the phrase 'artificial intelligence'. Most histories treat it as the moment AI became a research field of its own. of summer 1956 launched the field under that name. McCarthy later recalled choosing the term partly to set the new field apart from cyberneticscybernetics, n.: The study of how animals, machines and organizations steer themselves using feedback: sensing the result of an action and correcting course. It was both a parent and an early rival of AI. and automata theory. Alan Turing's earlier writing (1948–1950) spoke of intelligent machinery and thinking machines.

Usage note

Definitions are notoriously unstable: once a task is solved it often stops being called AI (the AI effectAI effect, n.: The habit of deciding that once a computer can do something — play chess, recognize speech, translate — it no longer counts as real intelligence, so the label keeps moving on to tasks machines cannot manage yet.). Not to be confused with artificial general intelligenceartificial general intelligence, n.: AI that could learn and do almost any mental task a capable adult can, rather than excelling at one narrow job. Experts disagree on the exact bar and on when, or whether, it will arrive., a system matching or exceeding humans across most cognitive tasks; whether any current system qualifies is disputed. Since Executive Order 14434Executive Order 14434, prop. n.: A September 2026 order by US President Donald Trump telling federal agencies to say 'super intelligence' (SI) instead of 'artificial intelligence' (AI) in official documents and communications. (29 September 2026), US federal agencies are directed to use 'Super Intelligence' (SI) in place of 'artificial intelligence' in their non-statutory communications; the statutory definition is unchanged.

Sources

McCarthy, J., Minsky, M. L., Rochester, N. & Shannon, C. E. (1955). A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence. jmc.stanford.edu/articles/dartmouth/dartmouth.pdf
Russell, S. & Norvig, P. (1995; 4th ed. 2020). Artificial Intelligence: A Modern Approach. Prentice Hall/Pearson.

Defined in law or standards

15 U.S.C. § 9401(3) (US National Artificial Intelligence Initiative Act of 2020); for 'AI system' see EU AI Act (Reg. (EU) 2024/1689), Art. 3(1)

Mentioned in

AI governanceAI governance, n.: The rules, institutions and habits that shape how AI is built and used — from laws and treaties to technical standards and a company's own review processes., Alan TuringAlan Turing, prop. n.: A British mathematician who worked out what computers can do in principle, helped break German codes in the Second World War, and proposed the best-known test of machine intelligence., generative AIgenerative AI, n.: AI that produces something new on request, such as an essay, a picture, a song or a piece of code, having absorbed from enormous numbers of existing examples what such things typically look like., intelligenceintelligence, n.: The ability to learn, understand, reason and solve problems — especially new ones — in order to reach goals. Experts disagree about how to define it precisely, for people and even more for machines., machine learningmachine learning, n.: A way of building software that learns from examples instead of following rules written by a programmer. Shown thousands of labeled photos, for instance, a program can learn to recognize cats., roboticsrobotics, n.: The science and engineering of building robots and making them work: designing their bodies, sensors and motors, and writing the software that lets them see, plan and move safely., superintelligencesuperintelligence, n.: A mind, usually imagined as an AI, that would leave even the cleverest people far behind in nearly every kind of thinking, not just in one game or skill. None is known to exist., symbolic AIsymbolic AI, n.: An approach to AI that writes knowledge down as human-readable symbols and rules, such as 'every bird has wings', and reasons by manipulating them step by step instead of learning patterns from data., AI effectAI effect, n.: The habit of deciding that once a computer can do something — play chess, recognize speech, translate — it no longer counts as real intelligence, so the label keeps moving on to tasks machines cannot manage yet., AI-poweredAI-powered, adj.: Described as using artificial intelligence to work. The label appears on everything from search engines to toothbrushes and often says little about how much AI is really involved., Computing Machinery and IntelligenceComputing Machinery and Intelligence, prop. n.: Alan Turing's 1950 essay asking whether machines can think. It proposed a conversation test in place of that question, answered objections to thinking machines and suggested that machines might learn like children., cyberneticscybernetics, n.: The study of how animals, machines and organizations steer themselves using feedback: sensing the result of an action and correcting course. It was both a parent and an early rival of AI., Dartmouth workshopDartmouth workshop, prop. n.: A summer meeting of scientists at Dartmouth College in 1956, planned in a 1955 funding proposal that first used the phrase 'artificial intelligence'. Most histories treat it as the moment AI became a research field of its own., Executive Order 14434Executive Order 14434, prop. n.: A September 2026 order by US President Donald Trump telling federal agencies to say 'super intelligence' (SI) instead of 'artificial intelligence' (AI) in official documents and communications., intelligence augmentationintelligence augmentation, n.: Using computers to make people smarter and more capable rather than building machines that think on their own: AI as a tool for human minds., intelligent agentintelligent agent, n.: In AI theory, a decision-maker, such as a robot, a self-driving car, a chess program or a helpful piece of software, that notices what is going on around it and responds in ways that serve its goals., John McCarthyJohn McCarthy, prop. n.: The American computer scientist who coined the term 'artificial intelligence', invented the Lisp programming language and championed formal logic as the route to machine common sense., machine intelligencemachine intelligence, n.: Intelligence shown by machines; another name for artificial intelligence, preferred by some because it does not suggest that such intelligence is fake., philosophy of artificial intelligencephilosophy of artificial intelligence, n.: The branch of philosophy that asks what AI is and could be: whether machines can think, understand or be conscious, what intelligence is, and what we owe to and should expect from intelligent machines., The Last DictionaryThe Last Dictionary, prop. n.: This book: a dictionary of intelligence, human and otherwise, which explains each word first in plain language, then precisely, and says when it was born., computational intelligencecomputational intelligence, n.: A family of AI methods inspired by nature, such as neural networks, fuzzy logic and evolutionary algorithms, that learn or adapt from numbers rather than following explicit logical rules.